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An efficient architecture for adaptive progressive thresholding

Authors: Hui Tian; Siew Kei Lam; Thambipillai Srikanthan; Chip-Hong Chang;

An efficient architecture for adaptive progressive thresholding

Abstract

A new pipelined architecture for adaptive progressive thresholding (APT) is proposed. Unlike the conventional architectures that rely heavily on multipliers and dividers to evaluate the maximum between-class variance, our method employs a reconfigurable logarithmic computing unit to simplify the circuitry and increases the application's ability to handle operational variation. Our logarithmic conversion algorithm avoids large look-up tables by streaming the operand's bits into segments so that several small look-up tables and simple adders and shifters are sufficient to guarantee an accurate result. Besides being cost effective, the proposed architecture has also significantly reduced the latency of the critical pipelined stage.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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